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基于模糊广义系统技术的旋转倒立摆的鲁棒最优控制

Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques.

作者信息

Pham Duc-Binh, Dao Quy-Thinh, Bui Ngoc-Tam, Nguyen Thi-Van-Anh

机构信息

Hanoi University of Science and Technology, Hanoi, 11615, Vietnam.

Innovative Global Program, Shibaura Institute of Technology, Saitama, 337-8570, Japan.

出版信息

Sci Rep. 2024 Mar 7;14(1):5593. doi: 10.1038/s41598-024-56202-2.

DOI:10.1038/s41598-024-56202-2
PMID:38454029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10920893/
Abstract

Expanding upon the well-established Takagi-Sugeno (T-S) fuzzy model, the T-S fuzzy descriptor model emerges as a robust and flexible framework. This article introduces the development of optimal and robust-optimal controllers grounded in the principles of stability control and fuzzy descriptor systems. By transforming complicated inequalities into linear matrix inequalities (LMI), we establish the essential conditions for controller construction, as delineated in theorems. To substantiate the utility of these controllers, we employ the rotary inverted pendulum as a testbed. Through diverse simulation scenarios, these controllers, rooted in fuzzy descriptor systems, demonstrate their practicality and effectiveness in ensuring the stable control of inverted pendulum systems, even in the presence of uncertainties within the model. This study highlights the adaptability and robustness of fuzzy descriptor-based controllers, paving the way for advanced control strategies in complex and uncertain environments.

摘要

在成熟的高木-菅野（T-S）模糊模型基础上进行扩展，T-S模糊描述符模型成为一个强大且灵活的框架。本文介绍了基于稳定性控制原理和模糊描述符系统的最优和鲁棒最优控制器的发展。通过将复杂不等式转化为线性矩阵不等式（LMI），我们建立了控制器构造的必要条件，如定理中所描述。为了证实这些控制器的效用，我们将旋转倒立摆作为测试平台。通过各种仿真场景，这些基于模糊描述符系统的控制器展示了它们在确保倒立摆系统稳定控制方面的实用性和有效性，即使在模型存在不确定性的情况下也是如此。本研究突出了基于模糊描述符的控制器的适应性和鲁棒性，为复杂和不确定环境中的先进控制策略铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/108df67362b4/41598_2024_56202_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/0a3653452018/41598_2024_56202_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/108df67362b4/41598_2024_56202_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/4a2e6c13a4c8/41598_2024_56202_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/51e1fe94ba48/41598_2024_56202_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/9fbe8b17e704/41598_2024_56202_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/cf396cd1520d/41598_2024_56202_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/acbdf2c2f50d/41598_2024_56202_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/d8e70311e748/41598_2024_56202_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/8731d9875e3b/41598_2024_56202_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/bcf66eaedc82/41598_2024_56202_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/7fcef5cd70cd/41598_2024_56202_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/0f4a93708ad9/41598_2024_56202_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/0a3653452018/41598_2024_56202_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9723/10920893/108df67362b4/41598_2024_56202_Fig12_HTML.jpg

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Robust Optimal Control for the Vehicle Suspension System With Uncertainties.
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